dc.contributor.author | Bache, Ida Wolden | |
dc.contributor.author | Mitchell, James | |
dc.contributor.author | Ravazzolo, Francesco | |
dc.contributor.author | Vahey, Shaun P. | |
dc.date.accessioned | 2018-05-08T12:55:32Z | |
dc.date.available | 2018-05-08T12:55:32Z | |
dc.date.issued | 2009 | |
dc.identifier.isbn | 978-82-7553-513-7 | |
dc.identifier.issn | 1502-8143 | |
dc.identifier.uri | http://hdl.handle.net/11250/2497627 | |
dc.description.abstract | We argue that the next generation of macro modellers at Inflation Targeting central banks should adapt a methodology from the weather forecasting literature known as `ensemble modelling'. In this approach, uncertainty about model specifications (e.g., initial conditions, parameters, and boundary conditions) is explicitly accounted for by constructing ensemble predictive densities from a large number of component models. The components allow the modeller to explore a wide range of uncertainties; and the resulting ensemble `integrates out' these uncertainties using time-varying weights on the components. We provide two examples of this modelling strategy: (i) forecasting inflation with a disaggregate ensemble; and (ii) forecasting inflation with an ensemble DSGE. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Norges Bank | nb_NO |
dc.relation.ispartofseries | Working Papers;15/2009 | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.subject | JEL: C11 | nb_NO |
dc.subject | JEL: C32 | nb_NO |
dc.subject | JEL: C53 | nb_NO |
dc.subject | JEL: E37 | nb_NO |
dc.subject | JEL: E52 | nb_NO |
dc.subject | DSGE models | nb_NO |
dc.subject | ensemble modelling | nb_NO |
dc.subject | forecasting | nb_NO |
dc.subject | density combination | nb_NO |
dc.title | Macro Modelling with Many Models | nb_NO |
dc.type | Working paper | nb_NO |
dc.description.version | publishedVersion | nb_NO |
dc.subject.nsi | VDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212 | nb_NO |
dc.source.pagenumber | 26 | nb_NO |